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Optimal groundwater remediation with well location as a decision variable: Model development
Author(s) -
Wang Wen,
Ahlfeld David P.
Publication year - 1994
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/93wr03552
Subject(s) - discretization , mathematical optimization , groundwater flow , aquifer , hydrogeology , variable (mathematics) , interpolation (computer graphics) , groundwater , computer science , groundwater remediation , function (biology) , environmental remediation , mathematics , engineering , geotechnical engineering , animation , mathematical analysis , ecology , computer graphics (images) , contamination , evolutionary biology , biology
A new formulation for the optimal design of aquifer remediation strategies is presented in which the well location problem is solved by explicitly incorporating the spatial coordinates and pumping rates of wells as decision variables. The Hermite interpolation function is used to represent the well location as a continuous function of space and to facilitate the incorporation of a barrier function for containing the well location within the model domain. The management model combines the numerical simulation of groundwater flow and contaminant transport with optimization methods to select the optimal location and pump rate by moving each well within the problem domain unrestricted by nodal location. The details of the numerical implementation required to incorporate well locations as decision variables in a two‐dimensional Galerkin finite element discretization of the groundwater flow and contaminant transport equations are presented. The approach is contrasted with an optimization model for groundwater quality management in which optimal well locations are chosen from a number of preselected candidate locations. A simple hypothetical problem is solved to compare these two approaches and examine the numerical behavior of the new formulation. The results indicate that a formulation in which well location is a decision variable can be implemented and that improved solutions are possible. The results are also used to demonstrate how this approach can be used to solve problems in which the initial costs of well installation are included.